// XPath CheatSheet | |
// To test XPath in your Chrome Debugger: $x('/html/body') | |
// http://www.jittuu.com/2012/2/14/Testing-XPath-In-Chrome/ | |
// 0. XPath Examples. | |
// More: http://xpath.alephzarro.com/content/cheatsheet.html | |
'//hr[@class="edge" and position()=1]' // every first hr of 'edge' class |
""" | |
Inspired by http://code.activestate.com/recipes/578253-an-entry-with-autocompletion-for-the-tkinter-gui/ | |
Changes: | |
- Fixed AttributeError: 'AutocompleteEntry' object has no attribute 'listbox' | |
- Fixed scrolling listbox | |
- Case-insensitive search | |
- Added focus to entry field | |
- Custom listbox length, listbox width matches entry field width | |
- Custom matches function | |
""" |
assets | |
business | |
accounts receivable | |
bank | |
personal | |
accounts receivable | |
bank | |
cash | |
gifts | |
online |
# Install ARCH Linux with encrypted file-system and UEFI | |
# The official installation guide (https://wiki.archlinux.org/index.php/Installation_Guide) contains a more verbose description. | |
# Download the archiso image from https://www.archlinux.org/ | |
# Copy to a usb-drive | |
dd if=archlinux.img of=/dev/sdX bs=16M && sync # on linux | |
# Boot from the usb. If the usb fails to boot, make sure that secure boot is disabled in the BIOS configuration. | |
# Set swedish keymap |
import numpy as np | |
import matplotlib.pyplot as plt | |
from scipy.spatial import Voronoi | |
def voronoi_finite_polygons_2d(vor, radius=None): | |
""" | |
Reconstruct infinite voronoi regions in a 2D diagram to finite | |
regions. | |
Parameters |
For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.
A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s
# -*- coding: utf-8 -*- | |
import sys, os | |
sys.path.insert(0, os.path.abspath('extensions')) | |
extensions = ['sphinx.ext.autodoc', 'sphinx.ext.doctest', 'sphinx.ext.todo', | |
'sphinx.ext.coverage', 'sphinx.ext.pngmath', 'sphinx.ext.ifconfig', | |
'epub2', 'mobi', 'autoimage', 'code_example'] |
GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.